MRI-Feedback Control of Ultrasound Based Mechanical Fractionation of Biological Tissue

ABSTRACT

Disclosed herein are example embodiments of devices, systems, and methods for mechanical fractionation of biological tissue using magnetic resonance imaging (MRI) feedback control. The examples may involve displaying an image representing first MRI data corresponding to biological tissue, and receiving input identifying one or more target regions of the biological tissue to be mechanically fractionated via exposure to first ultrasound waves. The examples may further involve applying the first ultrasound waves and, contemporaneous to or after applying the first ultrasound waves, acquiring second MRI data corresponding to the biological tissue. The examples may also involve determining, based on the second MRI data, one or more second parameters for applying second ultrasound waves to the biological tissue, and applying the second ultrasound waves to the biological tissue according to the one or more second parameters.

CROSS-REFERENCE TO RELATED APPLICATIONS

This application claims the benefit of U.S. Provisional PatentApplication No. 62/181,448, filed on Jun. 18, 2015, the contents ofwhich are incorporated herein by reference in their entirety.

STATEMENT REGARDING FEDERALLY SPONSORED RESEARCH OR DEVELOPMENT

This invention was made with government support under Grant No. 2 R01EB007643-05, awarded by the National Institutes of Health. Thegovernment has certain rights in the invention.

BACKGROUND

Unless otherwise indicated herein, the materials described in thissection are not prior art to the claims in this application and are notadmitted to be prior art by inclusion in this section.

High intensity focused ultrasound (HIFU) is a medical technology capableof transcutaneously fractionating or ablating selected portions oftissue without damaging intervening or surrounding tissues. In most HIFUapplications, tissue is thermally ablated via heating caused byultrasound energy absorption. Various techniques exist for using HIFUwaves to fractionate, ablate, damage, or disintegrate diseasedbiological tissue or a foreign object within a patient. Morespecifically, energy carried by HIFU waves may be absorbed by a targetregion of tissue or absorbed by an object, so that the temperature ofthe target region or object is increased, causing thermal ablation. HIFUwaves can also be sequentially focused (e.g., deflected or scanned) upondifferent target regions so that a larger macroscopic region of tissueor a large object may be thermally ablated. Techniques for HIFU-inducedmechanical fractionation exist as well.

SUMMARY

In one example, a method includes displaying, via a user interface, animage representing first magnetic resonance imaging (MRI) datacorresponding to biological tissue. The method further includesreceiving, via the user interface, first input identifying one or moretarget regions of the biological tissue to be mechanically fractionatedvia exposure to first ultrasound waves. The method further includesapplying the first ultrasound waves to the one or more target regions,thereby mechanically fractionating at least a portion of the one or moretarget regions. The first ultrasound waves are applied according to oneor more first parameters. The method further includes, contemporaneousto or after applying the first ultrasound waves, acquiring second MRIdata corresponding to the biological tissue. The method further includesdetermining, based on the second MRI data, one or more second parametersfor applying second ultrasound waves to the biological tissue. Themethod further includes applying the second ultrasound waves to thebiological tissue according to the one or more second parameters.

In another example, a non-transitory computer readable medium storesinstructions that, when executed by a device, cause the device toperform functions. The functions include displaying, via a userinterface of the device, an image representing first magnetic resonanceimaging (MRI) data corresponding to biological tissue. The functionsfurther include receiving, via the user interface, first inputidentifying one or more target regions of the biological tissue to bemechanically fractionated via exposure to first ultrasound waves. Thefunctions further include applying, via a transducer of the device, thefirst ultrasound waves to the one or more target regions, therebymechanically fractionating at least a portion of the one or more targetregions. The first ultrasound waves are applied according to one or morefirst parameters. The functions further include, contemporaneous to orafter applying the first ultrasound waves, acquiring, via an MRI imagingsystem of the device, second MRI data corresponding to the biologicaltissue. The functions further include determining, based on the secondMRI data, one or more second parameters for applying second ultrasoundwaves to the biological tissue. The functions further include applying,via the transducer, the second ultrasound waves to the biological tissueaccording to the one or more second parameters.

In yet another example, a device includes one or more processors, a userinterface, a transducer, a magnetic resonance imaging (MRI) system, anda non-transitory computer readable medium storing instructions that,when executed by the one or more processors, cause the device to performfunctions. The functions include displaying, via the user interface, animage representing first MRI data corresponding to biological tissue.The functions further include receiving, via the user interface, firstinput identifying one or more target regions of the biological tissue tobe mechanically fractionated via exposure to first ultrasound waves. Thefunctions further include applying, via the transducer, the firstultrasound waves to the one or more target regions, thereby mechanicallyfractionating at least a portion of the one or more target regions. Thefirst ultrasound waves are applied according to one or more firstparameters. The functions further include, contemporaneous to or afterapplying the first ultrasound waves, acquiring, via the MRI imagingsystem, second MRI data corresponding to the biological tissue. Thefunctions further include determining, based on the second MRI data, oneor more second parameters for applying second ultrasound waves to thebiological tissue. The functions further include applying, via thetransducer, the second ultrasound waves to the biological tissueaccording to the one or more second parameters.

When the term “substantially” or “about” is used herein, it is meantthat the recited characteristic, parameter, or value need not beachieved exactly, but that deviations or variations, including forexample, tolerances, measurement error, measurement accuracy limitationsand other factors known to those of skill in the art, may occur inamounts that do not preclude the effect the characteristic was intendedto provide. In some examples disclosed herein, “substantially” or“about” means within +/−5% of the recited value.

These as well as other aspects, advantages, and alternatives will becomeapparent to those of ordinary skill in the art by reading the followingdetailed description, with reference where appropriate to theaccompanying drawings. Further, it should be understood that thissummary and other descriptions and figures provided herein are intendedto illustrate the invention by way of example only and, as such, thatnumerous variations are possible.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 is a schematic diagram of a device configured for mechanicalfractionation of biological tissue or other objects, in accordance withexample embodiments.

FIG. 2 is a flow chart depicting an example method for mechanicalfractionation of a volume within biological tissue or other objects, inaccordance with example embodiments.

FIG. 3 is a simplified depiction of an image of biological tissuedisplayed by a user interface, in accordance with example embodiments.

FIG. 4 is a simplified depiction of an image of biological tissue withtarget regions that have been selected for mechanical fractionation, inaccordance with example embodiments.

FIG. 5 is an illustration of emitted ultrasound pulses defined byseveral parameters, in accordance with example embodiments.

FIG. 6 is a simplified depiction of an image of biological tissue thathas undergone a portion of a mechanical fractionation procedure, inaccordance with example embodiments.

FIG. 7 is a simplified depiction of an image of biological tissue withavoidance regions that have been selected for monitoring duringmechanical fractionation of target regions, in accordance with exampleembodiments.

FIG. 8A is a T2-weighted MRI image of ex vivo bovine liver tissue in thecoronal image plane with target regions shown.

FIG. 8B is a T2-weighted MRI image of ex vivo bovine liver tissue in thesagittal image plane with target regions shown.

FIG. 9 is a real-time temperature map of ex vivo bovine liver tissue inthe coronal plane.

FIG. 10 is a graph depicting temperature over time for a region of theex vivo bovine liver tissue.

FIG. 11A is a real-time fast-field-echo (FFE) image of the ex vivobovine liver tissue in the coronal plane.

FIG. 11B is a real-time FFE image of the ex vivo bovine liver tissue inthe sagittal plane.

FIG. 12A is a real-time FFE image of the ex vivo bovine liver tissueshowing one volumetric sonication.

FIG. 12B is a real-time FFE image of the ex vivo bovine liver tissueshowing two volumetric sonications.

FIG. 12C is a real-time FFE image of the ex vivo bovine liver tissueshowing three volumetric sonications.

FIG. 12D is a real-time FFE image of the ex vivo bovine liver tissueshowing four volumetric sonications.

FIG. 13A is an FFE image of ex vivo bovine liver tissue after a firstsonication.

FIG. 13B is an FFE image of the ex vivo bovine liver tissue during asecond sonication.

FIG. 13C is an FFE image of the ex vivo bovine liver tissue after thesecond sonication.

FIG. 14 is a T2-weighted image of the ex vivo bovine liver tissue afterthe completion of a sonication therapy.

DETAILED DESCRIPTION

Although magnetic resonance imaging (MRI) and related MR diagnostictechniques can be used in conventional HIFU therapy, the purely thermalnature of conventional HIFU can limit the utility of MRI and MRtechniques for monitoring, control, and diagnostic evaluation of HIFUwhen applied clinically or even experimentally. The limitations arelargely due to diffusion of heat within biological tissue undergoingHIFU sonication. In particular, when biological tissue is subjected toHIFU sonication, diffusion of absorbed heat outward from a focal pointof the HIFU sonication may render lesion formation somewhat impreciseand/or unpredictable. For example, the boundary between thermallyablated biological tissue and undisturbed tissue may drift outward fromits intended location. Also, the boundary itself may lack sharpness,forming instead a possibly undesirable gradual transition from fullyablated tissue to undisturbed tissue surrounding the ablated tissue.

One result of the somewhat imprecise nature of conventional HIFU-inducedlesion formation in biological tissue is a correspondingly impreciseability to monitor and control lesion formation using HIFU in the firstplace. Another result is that MRI and MR techniques used in conjunctionwith HIFU for the purpose of control and evaluation of results canthemselves be limited by gradation of contrast changes across lesionboundaries, for example. This, in turn, may diminish the evaluativeutility of MR data acquired during and/or after HIFU sonication.Furthermore, the duration over which sonication induced heat diffusesaway from the target region of the biological tissue may extend beyondthe duration over which HIFU sonication is actually applied to thetarget region. Consequently, the volumetric extent of lesion formationmay not be known until some time after HIFU sonication ceases. This canlimit the utility of MRI and MR techniques for real-time monitoring ofthe effects of HIFU during sonication; the viability of evaluating thefinal lesion size may be similarly constrained.

Accordingly, there is a need for techniques that improve monitoring,control, and evaluation of HIFU-based targeted ablation or fractionationof biological tissue.

As such, an example method includes displaying, via a user interface, animage representing first magnetic resonance imaging (MRI) datacorresponding to biological tissue. The method further includesreceiving, via the user interface, first input identifying one or moretarget regions of the biological tissue to be mechanically fractionatedvia exposure to first ultrasound waves. The method further includesapplying the first ultrasound waves to the one or more target regions,thereby mechanically fractionating at least a portion of the one or moretarget regions. The first ultrasound waves may be applied according toone or more first parameters. The method further includes,contemporaneous to or after applying the first ultrasound waves,acquiring second MRI data corresponding to the biological tissue. Themethod further includes determining, based on the second MRI data, oneor more second parameters for applying second ultrasound waves to thebiological tissue. The method further includes applying the secondultrasound waves to the biological tissue according to the one or moresecond parameters.

Disclosed herein are methods and devices for employing a noveladaptation of conventional HIFU that provides for better control andprecision in targeted HIFU-induced ablation or fractionation ofbiological tissue. In accordance with example embodiments, HIFU may beadapted to cause targeted and controlled destruction of biologicaltissue by mechanical fractionation instead of by pure thermal ablation.This mechanical fractionation technique may enable destruction of one ormore target regions of biological tissue with improved control. Thetechnique may enable better control of the size and shape of the ablatedportion of tissue, and better control of the location and definition ofthe boundary between ablated and non-ablated tissue. Post-sonicationheat diffusion can typically be better managed via this mechanicalfractionation technique.

In an example embodiment, an adapted HIFU technique termed “boilinghistotripsy” (BH) is used for generating mechanically fractionatedlesions in biological tissue. BH is a therapeutic technique in whichlesions can be purely mechanical in origin, i.e. liquefied, or, inaddition to mechanical fractionation, include different degrees ofthermal effect controlled by the parameters of an ultrasound exposure(sonication) protocol. Specifically, the peak output power, resultant insitu shock amplitude, ultrasound frequency, pulse length, pulserepetition rate, number of pulses, and sonication trajectory can beadjusted.

In one example demonstration, BH sonication was performedvolumetrically, i.e., involving concurrently or sequentially sonicatingregions larger than a single focal point. In another exampledemonstration, various MRI methods were used to monitor BH sonication inreal time, as well as assess the therapy outcome.

MRI can provide in vivo anatomical, functional, and temperature images,as well as provide information on tissue displacement in real timeduring a HIFU sonication. While MRI-based feedback can be used tocontrol conventional MR-HIFU thermal ablation, (e.g., to achievecomplete thermal necrosis in the target region), as well as to controlconventional MR-HIFU mediated mild hyperthermia, these techniques relyon the monitoring of HIFU-induced temperature changes only.

The BH method can be used to induce mechanically-fractionated lesionswith a controlled degree of thermal effect. The technique may involverepetitive millisecond-long pulses with shocks, rapid localized boilingin tissue caused by shock wave heating, and interaction of shocks with avapor cavity. Such an approach can be advantageous for avoidingoverheating of vessels, bone, or other structures located close to thetreatment site. This approach may also accelerate resorption or passageof the ablated tissue volume, diminish pressure on the surroundingorgans that causes discomfort, and insert openings between tissues,among other desired effects or outcomes.

Some benefits enabled by BH are the ability to use MRI to accuratelyplan BH-sonications, to perform BH-therapy under real-time imagingguidance, and to evaluate the outcome of the treatment.

In conventional HIFU, the extent of a thermally coagulated region may beestimated based on accumulated thermal dose, and might not accuratelyreflect the final post-therapy outcome. Similarly, in mild hyperthermia,temperature in the target region may be elevated to 40-45° C. for aprolonged duration, after which the tissue is allowed to cool down. Theregion of mild hyperthermia may be estimated from the temperaturegradients and/or thermal dose over time. However, tissue contrastchanges are not easily seen via MR-imaging when used in conjunction witheither thermal ablation or mild hyperthermia.

In contrast, various MRI methods can be used during BH-mediatedmechanical tissue fractionation to monitor and control progress of BH inreal time based on tissue contrast changes. For example, during BHtherapy, real-time imaging findings can provide a basis for adjustingthe sonication power, duty cycle, duration, number of pulses, and/orsonication trajectory for more desirable results (e.g., full mechanicalfractionation of tissue at the target location). In addition tomonitoring contrast changes in real time, temperature can be monitoredsimultaneously inside and outside of the target region to avoidexceedingly high temperatures at the target as well as avoid temperatureelevations and tissue damage outside of the target region. Use of MRIand MR techniques in conjunction with BH (and HIFU histotripsy ingeneral) to plan, monitor, control, and evaluate BH-induced targeteddestruction of biological tissue prior to, during, and after BHsonication is referred to herein as “MRI-assisted BH.”

The term “biological tissue” is used herein to refer generically totissue such as human (or other animal) tissue and/or organs, as well asother tissue of biological origin. Biological tissue (human or other)can be part of a living or non-living subject. For example, in some ofthe discussions below, demonstration operations of MRI-assisted BH wereapplied to sample biological tissue including ex vivo bovine liver andheart tissue. Other non-limiting examples of “biological tissue” usedherein include liver tissue, uterine tissue, kidney tissue, prostatetissue, thyroid tissue, pancreas tissue, brain tissue, nerve tissue,connective tissue, fat tissue, or muscle tissue. Biological tissue canalso include a biological substance, such as a blood clot or a hematoma.

The terminology “targeted destruction of biological tissue” used hereinis generally synonymous with controlled and/or intentional lesionformation in tissue and/or organs, although the result of suchintentional “destruction of biological tissue” may not necessarily be alesion. Further, MRI-assisted BH can be applied to treatment ofpathological tissue, such as malignant tumors and/or benign tumors,where non-limiting examples of benign tumors include an adenoma or afibroid. Additionally, MRI-assisted BH can used to create and/or insertof openings in biological tissue for various therapeutic purposes.

It should be noted that various changes and modifications to thepresently preferred embodiments described herein will be apparent tothose skilled in the art. Such changes and modifications may be madewithout departing from the spirit and scope of the present invention andwithout diminishing its attendant advantages.

Referring now to the Figures, FIG. 1 illustrates an example device (orsystem) 100 configured to mechanically fractionate biological tissue 114(or other objects) using an acoustic ultrasound wave (or “HIFU” wave)113. The device 100 includes one or more processors 102, data storage104, a user interface 106, a signal generator 108, an ultrasoundtransducer 110, and a magnetic resonance imaging (MRI) system 116, anyor all of which may be communicatively coupled to each other via asystem bus or another connection mechanism 112.

The processor(s) 102 may include a general purpose processor and/or aspecial purpose processor and may be configured to execute programinstructions stored within data storage 104. In some examples, theprocessor(s) 102 may be a multi-core processor comprised of one or moreprocessing units configured to coordinate to execute instructions storedwithin data storage 104. In one example, the processor(s) 102, byexecuting program instructions stored within data storage 104, mayprovide ultrasound parameters to the signal generator 108 for generationof ultrasound waves. In another example, the processor(s) 102 mayprovide, to the signal generator 108, ultrasound parameters that arereceived via the user interface 106.

Data storage 104 may include one or more volatile, non-volatile,removable, and/or non-removable storage components. Data storage 104 mayinclude a magnetic, optical, or flash storage medium, and may beintegrated in whole or in part with the processor(s) 102 or otherportions of the device 100. Further, the data storage 104 may be anon-transitory computer-readable storage medium, having stored thereonprogram instructions that, when executed by the processor(s) 102, causethe device 100 to perform any function described in this disclosure.Such program instructions may be part of a software application that canbe executed in response to inputs received from the user interface 106,for instance. The data storage 104 may also store other types ofinformation or data, such as those types described throughout thisdisclosure.

The user interface 106 may enable interaction with a user of the device100, if applicable. The user interface 106 may include input componentssuch as a keyboard, a mouse, a keypad, a touchscreen, or atouch-sensitive panel, and output components such as a display screen(which, for example, may be combined with a touch-sensitive panel), asound speaker, or a haptic feedback system. In one example, the userinterface 106 may receive input indicating various parameters for anultrasound wave to be generated by the ultrasound transducer 110.

The signal generator 108 may be configured to receive, from theprocessor(s) 102, data indicative of ultrasound parameters forgeneration of an ultrasound wave by the ultrasound transducer 110. Forexample, the processor(s) 102 may send, to the signal generator 108,data representative of input received via the user interface 106. Inanother example, the received input may simply indicate one of severalpredetermined ultrasound fractionation protocols represented by programinstructions stored at data storage 104. In other instances, theultrasound fractionation protocols may be selected automatically by theprocessor(s) 102 based on MRI data received from the MRI imaging system116. Such data received by the signal generator 108 may indicate variousultrasound parameters such as power, power density, intensity,oscillation frequency, pulse duration, duty cycle, and a number ofpulses to be generated for various portions of the biological tissue114. The received data may also indicate a trajectory, path, or sequenceof portions of the biological tissue 114 upon which the focal point ofthe ultrasound wave may be sequentially directed upon. In some examples,multiple ultrasound beams may be focused on multiple regions of biologictissue simultaneously. The received data may also include timinginformation indicating when and/or for how long the focal point of theultrasound wave should be directed upon each respective portion of thebiological tissue 114.

The ultrasound transducer 110 may include an array of one or morepiezoelectric transducer elements or a lithotripter configured togenerate ultrasound or other acoustic waves in response to receivingcontrol signals representing ultrasound parameters from the signalgenerator 108. For example, the ultrasound transducer 110 may include aphased array of transducer elements configured to electronically focusor steer a generated ultrasound wave upon various portions of thebiological tissue 114 via constructive and/or destructive waveinterference. Each transducer element of the ultrasound transducer 110may receive its own independent control signal from the signal generator108. In some examples, the signal generator 108 and the ultrasoundtransducer 110 may be integrated into one functional unit. Theultrasound transducer 110 may include one or more of (i) a lens, (ii)one or more transducers having a radius of curvature at the focal pointof the ultrasound wave, and (iii) a phased array of transducers.

Some examples of forms the biological tissue 114 may take include atumor, a hematoma, an abscess, a lipoma, or any other diseased orundesirable tissue. The biological tissue may also include anycombination of one or more of the following types of tissues: liver,uterus, kidney, prostate, brain, breast, heart, blood vessel, lung, fat,nerve, or pancreas. Other examples are possible.

Generally, the device 100 may be used to fractionate any object ortissue. It should be assumed that for any example disclosed hereininvolving biological tissue, a generic object may be substituted inplace of the biological tissue. In these examples, the object might takethe form of a foreign object within a living body, but other examplesare possible.

The MRI Imaging system 116, as is known in the art, may includesuperconductive magnets, gradient coils, and/or RF transmission andreception coils, among other components. The MRI imaging system 116 maytake the form of a Philips Achieva 3T clinical MR scanner. In otherexamples, the MRI imaging system 116 may take the following forms aswell: Philips Ingenia, Philips Multiva, Siemens Magnetom, GE Signa, GEOptima, GE Discovery, Toshiba Vantage, Hitachi Echelon, or HitachiOasis. Other examples are possible. The MRI imaging system 116 may beconfigured to use the superconductive magnets (or other means) to applya static magnetic field to biological tissue or other material underexamination. The static magnetic field may align the spin of many ormost hydrogen nuclei (i.e., protons) within the biological tissue to beparallel with a single axis. (Nuclei of atoms other than hydrogen may beimaged as well.) The transmission coils (or other means) may be used toapply a time-varying (e.g., RF) magnetic field, thereby realigning thespins of at least some of the hydrogen nuclei away from the axis of thestatic field. When the RF field is relaxed, the reception coils (orother means) may detect RF waves emitted from the biological tissue asthe hydrogen nuclei relax to be again aligned with the static magneticfield. This process may be repeated periodically in real time togenerate images of the biological tissue. By mapping the RF data to thelocation at which it was detected, images can be generated by the MRIimaging system 116 and displayed by the user interface 106.

FIG. 2 is a flow chart depicting an example method 200 for mechanicallyfractionating biological tissue or other objects. The method 200depicted in FIG. 2 presents an example method that can be performedusing the device 100. In other examples, the method 200 may be performedvia any combination of suitable components described herein. FIG. 2 mayinclude one or more operations, functions, or actions as illustrated byone or more of blocks 202, 204, 206, 208, 210, and 212. Although theblocks are illustrated in a sequential order, these blocks may in someinstances be performed in parallel, and/or in a different order thanthose described herein. Also, the various blocks may be combined intofewer blocks, divided into additional blocks, and/or removed based uponthe desired implementation.

In addition, for the method 200, and other processes and methodsdisclosed herein, the flowcharts show functionality and operation of onepossible implementation of present embodiments. In this regard, eachblock may represent a module, a segment, or a portion of program code,which includes one or more instructions executable by a processor forimplementing specific logical functions or steps in a process. Theprogram code may be stored on any type of computer readable medium, forexample, such as a storage device including a disk or hard drive. Thecomputer readable medium may include a non-transitory computer readablemedium, for example, such as computer readable media that stores datafor short periods of time like register memory, processor cache, orRandom Access Memory (RAM). The computer readable medium may alsoinclude non-transitory media, such as secondary or persistent long termstorage, like read-only memory (ROM), optical or magnetic disks, orcompact-disc read-only memory (CD-ROM), for example. The computerreadable media may also be any other volatile or non-volatile storagesystem. The computer readable medium may be considered a computerreadable storage medium, a tangible storage device, or other article ofmanufacture, for example.

In addition, for the method 200, and other processes and methodsdisclosed herein, each block in FIG. 2 may represent circuitry that iswired to perform the specific logical functions in the process.

At block 202, the method 200 involves displaying, via a user interface,an image representing first magnetic resonance imaging (MRI) datacorresponding to biological tissue. As depicted in FIG. 3, for example,the user interface 106 may display an image 360 representing first MRIdata corresponding to the biological tissue 114. Prior to the userinterface 106 displaying the image 360, the MRI imaging system 116 mayacquire the first MRI data depicted by the image 360. In other examples,the first MRI data may be acquired by the MRI imaging system 116 oranother MRI system during a previous imaging session. As shown in FIG.3, the image 360 (i.e., the biological tissue 114) is arbitrarilyapportioned into regions 301-350 for the purpose of explaining conceptsbelow.

The first MRI data may include any combination of one or more of thefollowing: diffusion-weighted MRI data, tissue elasticity data,temperature data, T1-weighted data, T2-weighted data, proton densityweighted data, magnetic resonance elastography (MRE) data, magneticresonance acoustic radiation force imaging (MR-ARFI) data, T1 mappingdata, T2 mapping data, contrast-enhanced MRI data, tissue displacementdata, perfusion weighted imaging data, T2-star (T2*) weighted imagingdata, T2* mapping imaging data, an apparent diffusion coefficient (ADC)map, or thermal dosage data. The first MRI data may take other forms aswell.

At block 204, the method 200 involves receiving, via the user interface,first input identifying one or more target regions of the biologicaltissue to be mechanically fractionated via exposure to first ultrasoundwaves. For example, the user interface 106 may receive, via a mouse,touchscreen, or another user input device of the user interface 106,first input identifying portions 312, 313, 314, 322, 323, and 324 of thebiological tissue 114 for mechanical fractionation, as indicated byshading in FIG. 4.

Herein, the term “mechanical fractionation” may include processes inwhich ultrasound waves cause some degree of thermal ablation of thetargeted tissue or object, although in many instances it will bebeneficial if the damage inflicted on the targeted tissue or object ismostly mechanical in nature.

In some examples, the first input itself may indicate the respectiveboundaries of the regions 312, 313, 314, 322, 323, and 324. Forinstance, a user might use a mouse or a touchscreen to encirclerespective boundaries of the regions 312, 313, 314, 322, 323, and 324.In another example, the first input might indicate a perimeter thatcollectively encircles the regions 312, 313, 314, 322, 323, and 324. Inother examples, the first input may indicate a selection of apre-defined boundary template whereby the first input also indicatespositioning of the predefined boundary template upon the image 360. Inaccordance with the example of FIG. 4, the first input might take theform of a selection of a pre-defined rectangular boundary. The firstinput might further indicate a size and a desired position of thepre-defined boundary (e.g., via a click and drag gesture). In otherexamples, the user-defined boundary might be circular or take othershapes as well. Although not depicted in FIG. 4, the one or more targetregions may, in practice, take the form of one or more target volumes.That is, the first input may indicate one or more three-dimensionalregions for mechanical fractionation. In this context, the userinterface 106 may display images of the biological tissue 114 in morethan one image plane to facilitate selection of three-dimensionalvolumes of the biological tissue 114.

At block 206, the method 200 involves applying the first ultrasoundwaves to the one or more target regions, thereby mechanicallyfractionating at least a portion of the one or more target regions.Mechanical fractionation may be intended to include physical effectssuch as liquification and/or deformation of tissues or objects, amongother physical effects. Mechanical fractionation may occur via boilinghistotripsy and/or cavitation histotripsy, among other techniques. Thefirst ultrasound waves may be applied using the ultrasound transducer110, for example. The first ultrasound waves may take the form of a beamthat is selectively and/or sequentially focused upon the regions 312,313, 314, 322, 323, and 324. In this context, the first ultrasound wavesmay be applied according to one or more first parameters.

The one or more first parameters of the first ultrasound waves mayinclude any combination of one or more of: a sonication trajectory(e.g., path), a sequence upon which the first ultrasound waves arefocused respectively upon each of the one or more target regions, aquantity of consecutive or non-consecutive pulses that may be focusedrespectively upon each of the one or more target regions, pulsedurations, duty cycle, pulse repetition frequency, oscillationfrequency, power level, or intensity. The one or more first parametersmay be indicated as part of the first input received via the userinterface 106, but other examples are possible.

FIG. 5 depicts some example parameters that may define the firstultrasound waves (or the second ultrasound waves discussed below).Ultrasound waves 500 may take the form of one or more pulses, such aspulses 502, 504, and 506. Each of the pulses 502-506 may have anoscillation frequency f_(osc), pulse duration t₁, pulse repetitionfrequency f₂, and/or a duty cycle t₁/t₂ as illustrated by FIG. 5. Thepulses 502-506 may have a power level defined at least in part by anamplitude “A.” A power density level (e.g., intensity, W/cm²) definingthe pulses 502-506 may also account for the spatial distribution of theultrasound power embodied by the pulses 502-506 (e.g., beamwidth).

At block 208, the method 200 involves, contemporaneous to or afterapplying the first ultrasound waves, acquiring second MRI datacorresponding to the biological tissue. The acquired second MRI data mayreflect physical effect(s), if any, that the first ultrasound waves haveupon the biological tissue 114. Acquiring the second MRI data (or thefirst MRI data) may include any technique known in the art for using anMRI imaging system, the technique being suitable for acquiring the manyforms MRI data may take as described above.

At block 210, the method 200 involves determining, based on the secondMRI data, one or more second parameters for applying second ultrasoundwaves to the biological tissue. In many cases, the second ultrasoundwaves might be applied immediately after the first ultrasounds waves,reflecting a real-time MRI feedback process. In one example,fractionation of the one or more target regions may be proceeding asexpected, and the one or more second parameters might be selected to bethe same as the one or more first parameters. That is, it may bedetermined that no corrective action is required based on monitoring ofthe progress of the fractionation of the biological tissue 114 via thefirst ultrasound waves. In other examples, fractionation of the one ormore target regions via the first ultrasound waves might not beproceeding as expected, and a suitable adjustment to the sonicationtrajectory or parameters may be in order. The determined one or moresecond parameters may include parameters similar to any of the examplesprovided above for the one or more first parameters of the firstultrasound waves. In some examples, the one or more second parametersmay be indicated by second input received via the user interface 106(e.g., after viewing of the effects of the first ultrasound waves) andthe processor may assign the one or more second parameters to the secondultrasound waves accordingly.

FIG. 6 shows the user interface 106 displaying an image 380. The image380 may be a real-time MRI image of the biological tissue 114 as theultrasound waves 500 are being applied to the target region 312 of thebiological tissue 114. In other examples, the image 380 may be an imageof the biological tissue 114 sometime after the first ultrasound waveshave been applied to the biological tissue 114. FIG. 6 depicts theregion 312 as being at least partially mechanically fractionated.

In some examples, a user might view the image 380 and determine the oneor more second parameters for upcoming sonication based on certaincharacteristics of the biological tissue 114 shown in the image 380. Forinstance, the user might decide that the first ultrasound wavesfractionated the region 312 too quickly, and decide that the secondultrasound waves should be applied to the region 313 with a lower powersetting than the first ultrasound waves. In another example, the usermight determine that the focus of the first ultrasound waves is too wideand decide that the focus of the second ultrasound waves should benarrower than the first ultrasound waves.

In yet another example, the user might operate the ultrasound transducer110 according to three criteria: (1) stopping or pausing sonication ofthe region 312 or refocusing ultrasound waves upon another target regionof the treatment trajectory if an MRI signal intensity corresponding tothe region 312 exceeds a threshold corresponding to a suitable degree ofmechanical fractionation, (2) stopping or pausing sonication if atemperature indicated by the second MRI data indicates a temperature ofthe biological tissue 114 that exceeds a threshold temperature, and (3)stopping sonication of the biological tissue 114 as a whole if a maximumduration of sonication is exceeded. Many other examples are possible. Inthe absence of detecting an event like those described above, sonicationmay proceed according to the one or more first parameters withoutadjustment. In other examples, the processor(s) 102 may automaticallymake such determinations and adjust the sonication protocol accordingly.That is, the one or more second parameters for the second ultrasoundwaves may be determined either automatically by the processor(s) 102 ormanually via input received by the user interface 106.

Ultrasound parameters may be adjusted based on many other actioncriteria as well. Such parameters may include any combination of one ormore of peak output power, peak acoustic pressure (e.g., either at thefocus or at the transducer), oscillation frequency, duty cycle, pulseduration, pulse repetition rate, or trajectory. Other examples arepossible.

In some examples, the first input received by the user interface 106 mayalso indicate one or more characteristics of the second MRI data forevaluation. For example, the first input might indicate (1) MRI signalintensity of region 312 and (2) the temperature of the region 338indicated by the second MRI data as criteria of the second MRI data tobe evaluated. The first input may further include commands to: (1) stopor pause sonication of the region 312 or refocus ultrasound waves uponanother target region of the treatment trajectory if the MRI signalintensity corresponding to the region 312 exceeds a thresholdcorresponding to a suitable degree of mechanical fractionation, (2) stopor pause sonication if the temperature corresponding to target region338 exceeds a threshold temperature, and (3) stopping sonication of thebiological tissue 114 as a whole if a maximum duration of sonication isexceeded. The processor(s) 102 may determine the one or more secondparameters based on evaluating the characteristics of the second MRIdata identified by the first input. Such characteristics of the secondMRI data may include signal intensity, proton signal intensity, T1signal intensity, T2 signal intensity, indicated temperature, indicatedtissue diffusivity, indicated tissue elasticity, or indicated tissuedeformation. The one or more second parameters may also be determinedbased on a total ultrasound exposure duration or a total sonicationenergy absorbed by the biological tissue.

At block 212, the method 200 involves applying the second ultrasoundwaves to the biological tissue according to the one or more secondparameters. Block 212 may be similar to block 206 with the possibleexception that the one or more second parameters might be different fromthe one or more first parameters as described above. In other examples,the one more first parameters might be equal to the one or more secondparameters.

Additional features of example embodiments are described below. FIG. 7shows an image 390 of the biological tissue 114. Avoidance regions 328,329, 338, and 339 are shown in a shade of gray that is darker than thatof the target regions 312, 313, 314, 322, 323, and 324. In someexamples, the avoidance regions 328, 329, 338, and 339 may includetissues such as bone, muscle, skin, blood vessels, nerves, bowels,lungs, or other organs for which sonication is not intended and forwhich overheating or other damage is undesirable.

In some examples, characteristics of a portion of the second MRI datacorresponding to the avoidance regions 328, 329, 338, and 339 may beevaluated. This may involve characteristics such as signal intensity,proton signal intensity, T1 signal intensity, T2 signal intensity,indicated temperature, indicated tissue diffusivity, indicated tissueelasticity, or indicated tissue deformation.

By further example, the first input received by the user interface 106may also indicate the avoidance regions 328, 329, 338, and 339 asregions to be monitored while the target regions 312, 313, 314, 322, 323are sonicated. The input identifying the avoidance regions may besimilar to the input that indicates the target regions 312, 313, 314,322, 323, and 324. The first input may further indicate particularcharacteristics of the MRI data corresponding to the avoidance regions328, 329, 338, and 339 to be evaluated.

For instance, the first input may further indicate that a signalintensity of the second MRI data corresponding to the avoidance region338 should be monitored. As sonication of the target regions 312, 313,314, 322, 323, and 324 proceeds, the processor may evaluate the MRI datacorresponding to the avoidance region 338 in real-time, and may pausesonication or redirect the ultrasound beam if the signal intensitycorresponding to the avoidance region 338 exceeds a threshold value. Inanother example, the processor may evaluate the MRI data correspondingto the avoidance region 338 in real-time, and may pause sonication orredirect the beam (e.g., away from the avoidance region 338) if thetemperature corresponding to the avoidance region 338 exceeds athreshold temperature (e.g., 43° C.).

The following is description of another example that utilizes some ofthe concepts described above. One of skill in the art will realize thatmany other examples are contemplated herein.

First, a user may use the MRI imaging system 116 to acquire MRI datacorresponding to a biological tissue. The user interface 106 may displayan image representing the acquired MRI data. Next, the user may provideinput via the user interface 106 indicating a two-dimensional orthree-dimensional region of interest (ROI) of approximately 1 cm indiameter, centered on a target location. The processor(s) 102 maygenerate (e.g., calculate) one or more treatment trajectories forboiling histotripsy within the ROI, with user-prescribed separationbetween the points and trajectories. The user interface 106 might alsoreceive input indicating two-dimensional ROIs in the near field, and inthe far field, to indicate regions in which high temperature elevationsshould be avoided. The processor(s) 102 may use these latter ROIs todefine avoidance regions.

A sonication protocol may be determined such that if a T1 signalintensity of the ROI in the target region exceeds a threshold signalintensity, the ultrasound transducer 110 may halt sonication. In asimilar fashion, if signals corresponding to temperatures that exceed athreshold are detected from the avoidance regions, the ultrasoundtransducer 110 may halt sonication. Lastly, the ultrasound transducer110 may halt sonication if a total sonication duration exceeds athreshold duration. Input received by the user interface 106 may definethe threshold signal intensity, the threshold temperature, and/or thethreshold duration discussed above. The input received via the userinterface 106 may also define any other parameter that characterizesultrasound waves to be generated during the sonication.

As the sonication begins, the processor(s) 102 receives MRI dataacquired by the MRI imaging system 116. The processor(s) 102 adjusts theparameters of the sonication based on the acquired MRI data and causesthe ultrasound transducer 110 to sonicate the biological tissue 114accordingly. The processor(s) 102 may repeatedly use the acquired MRIdata to compare the actual T1 signal intensity within the target regionto the predetermined minimum T1 signal intensity. The processor(s) 102may also repeatedly use the acquired MRI data to compare the actualtemperature of the avoidance region to the predetermined thresholdtemperature. The processor(s) 102 may repeatedly modify the sonicationprotocol according to the criteria defined above.

FIGS. 8-14 illustrate experiments that were performed to demonstrate thefunctionality of the aforementioned methods, devices, and systems.

FIG. 8A is a coronal cross-section of a portion of ex vivo bovine livertissue. FIG. 8B is a sagittal cross-section of the same liver tissuethat is depicted in FIG. 8A. The images of FIGS. 8A and 8B were used toplan an experimental protocol for sonicating the liver tissue. Theultrasound beam generated by a transducer was steered from left to rightwith respect to FIG. 8B. The images of FIGS. 8A and 8B can be used forplanning of a sonication therapy. For example, regions-of-interest (ROI)for feedback control can be defined both within the target region(depicted by rectangles and circles) and/or outside of the targetregion. For example, an ROI within the target region can be used to stoptherapy once the diameter of the lesion as seen in real time exceeds 1cm. Similarly, an ROI in the near field can be used to pause therapyonce the temperature within this ROI exceeds, e.g., 43 C. The volume ofthe ROIs in this example are 10×10×15 mm.

FIG. 9 is a real time temperature map in the coronal image plane duringa BH-sonication of the ex vivo bovine liver tissue described above.Temperature at the target location as well as in surrounding regions canbe monitored in real time. This information can be utilized inclosed-loop or user adjustable feedback control to avoid off-targettemperature elevations and to perform safer treatments, as well as tocontrol temperatures at the target. Different temperature limits andactions can be applied to different regions within the image using ROIs,action criteria, and logical conditions (e.g., AND, NAND, OR, NOR, XOR,etc.).

FIG. 10 depicts temperatures at the target, calculated from the realtime temperature maps during a BH-sonication within the ex vivo bovineliver. Curves show a maximum temperature, mean temperature in a 10×10 mmROI centered on the target, and the standard deviations. Similar curvescan be calculated from regions outside of the target. This informationcan be used in closed-loop or user-adjustable feedback control to changetarget location of an ultrasound beam or to adjust sonication parametersto regulate temperatures both within and outside of the target region.Different temperature limits and actions can be applied to differentregions within the image using ROIs, action criteria, and logicalconditions. In this example, sonication was switched to another location(layer) by an automatic feedback algorithm at 800 seconds when the meantemperature at the target reached 38° C.

FIG. 11A shows real time fast-field-echo (FFE) magnitude images during aBH-sonication within the ex vivo bovine liver in the coronal imagingplane. FIG. 11B shows the same information in the sagittal imagingplane. A transducer sonicates from left to right in the sagittal image.BH-lesion formation (indicated by arrows), corresponding to the plannedlocations and feedback ROIs, can be visualized in real time in these FFEimages. This information can be utilized to control or limit off-targetlesion formation to perform safer treatments, as well as to control thetarget region location, shape, size, and degree of homogenization orfractionation in real time. Different limits of signal intensity orelasticity change can be applied to different regions within the imageusing ROIs, action criteria, and logical conditions, based on baselineMRI signal intensity or elasticity measurements.

FIGS. 12A, 12B, 12C, and 12D are real time FFE magnitude images capturedduring a BH-sonication of the ex vivo bovine liver. The images representthe coronal imaging plane. BH-lesion formations, corresponding to thetarget locations and feedback ROIs, can be visualized in real time inthese FFE images. FIG. 12A shows the ex vivo liver tissue after onevolumetric BH sonication. FIG. 12B shows the liver tissue after twovolumetric BH sonications. FIG. 12C shows the liver tissue after threevolumetric BH sonications. FIG. 12D shows the liver tissue after fourvolumetric BH sonications. Unlike in ultrasound applications such asthermal ablation and mild hyperthermia that are purely thermal innature, the BH lesions are clearly visible in real time MRI, and alsopersistent on MR images acquired post-sonication. This information isuseful since feedback control can be performed not only based on thecurrent target region that is being sonicated, but also on the previoustargets and ROIs.

FIGS. 13A, 13B, and 13C are real time FFE magnitude images during aBH-sonication of the ex vivo bovine liver in the sagittal imaging plane.BH-lesion formations, corresponding to the planned locations andfeedback ROIs, can be visualized in real time in these FFE images. FIG.13A shows the liver tissue after one volumetric BH sonication, but priorto starting a second volumetric BH sonication. FIG. 13B shows the livertissue during a second volumetric BH sonication. FIG. 13C shows theliver tissue after completion of the second volumetric BH sonication. Asshown in FIG. 13B, the mean signal intensity (indicated by an arrow)wasn't yet at a level corresponding to the action criteria, and thus thesonication was continued according to an automatic feedback algorithm.As shown in FIG. 13C, the sonication was stopped according to thefeedback algorithm when the mean signal intensity within the ROIexceeded a threshold and thus the action criterion was fulfilled.

FIG. 14 is a T2-weighted image captured after a BH-sonication of the exvivo bovine liver tissue in the coronal imaging plane. BH-lesionlocations, shapes, and sizes, corresponding to the planned locations andfeedback ROIs, can be visualized and measured post-therapy, even withoutusing MRI contrast agents. This information can be used to assesspost-therapy outcomes and used in closed-loop or user-adjustablefeedback control. For example, the information on lesion location,shape, size, and signal intensity when compared to neighboring tissuecan be used to plan subsequent sonications aimed toward merging existinglesions into one contiguous lesion, re-treat a lesion, or to make adecision to treat other targets or to end treatment. DifferentMR-imaging methods may be needed to provide adequate contrast forspecific tissue types.

While various example aspects and example embodiments have beendisclosed herein, other aspects and embodiments will be apparent tothose skilled in the art. The various example aspects and exampleembodiments disclosed herein are for purposes of illustration and arenot intended to be limiting, with the true scope and spirit beingindicated by the following claims.

1-336. (canceled)
 337. A method comprising: displaying, via a userinterface, an image representing first magnetic resonance imaging (MRI)data corresponding to biological tissue; receiving, via the userinterface, first input identifying one or more target regions of thebiological tissue to be mechanically fractionated via exposure to firstultrasound waves; applying the first ultrasound waves to the one or moretarget regions, thereby mechanically fractionating at least a portion ofthe one or more target regions, wherein the first ultrasound waves areapplied according to one or more first parameters; contemporaneous to orafter applying the first ultrasound waves, acquiring second MRI datacorresponding to the biological tissue; determining, based on the secondMRI data, one or more second parameters for applying second ultrasoundwaves to the biological tissue; and applying the second ultrasound wavesto the biological tissue according to the one or more second parameters.338. The method of claim 337, further comprising: prior to displayingthe image, acquiring the first MRI data by using an MRI system.
 339. Themethod of claim 1, further comprising: receiving, via the userinterface, second input that identifies the one or more secondparameters, wherein the one or more second parameters are determinedbased on the received second input.
 340. The method of claim 1, whereinthe one or more second parameters are equal to the one or more firstparameters.
 341. The method of claim 1, wherein at least one parameterof the one or more second parameters is not equal to a correspondingparameter of the one or more first parameters.
 342. The method claim 1,wherein the second MRI data indicates a change in signal intensity incomparison to the first MRI data.
 343. A non-transitory computerreadable medium storing instructions that, when executed by a device,cause the device to perform functions comprising: displaying, via a userinterface of the device, an image representing first magnetic resonanceimaging (MRI) data corresponding to biological tissue; receiving, viathe user interface, first input identifying one or more target regionsof the biological tissue to be mechanically fractionated via exposure tofirst ultrasound waves; applying, via a transducer of the device, thefirst ultrasound waves to the one or more target regions, therebymechanically fractionating at least a portion of the one or more targetregions, wherein the first ultrasound waves are applied according to oneor more first parameters; contemporaneous to or after applying the firstultrasound waves, acquiring, via an MRI imaging system of the device,second MRI data corresponding to the biological tissue; determining,based on the second MRI data, one or more second parameters for applyingsecond ultrasound waves to the biological tissue; and applying, via thetransducer, the second ultrasound waves to the biological tissueaccording to the one or more second parameters.
 344. The non-transitorycomputer readable medium of claim 343, the functions further comprising:prior to displaying the image, acquiring the first MRI data by using theMRI imaging system.
 345. The non-transitory computer readable medium ofclaim 343, the functions further comprising: receiving, via the userinterface, second input that identifies the one or more secondparameters, wherein the one or more second parameters are determinedbased on the received second input.
 346. The non-transitory computerreadable medium of claim 343, wherein the one or more second parametersare equal to the one or more first parameters.
 347. The non-transitorycomputer readable medium of claim 343, wherein at least one parameter ofthe one or more second parameters is not equal to a correspondingparameter of the one or more first parameters.
 348. The non-transitorycomputer readable medium of claim 343, wherein the second MRI dataindicates a change in signal intensity in comparison to the first MRIdata.
 349. A device comprising: one or more processors; a userinterface; a transducer; a magnetic resonance imaging (MRI) system; anda non-transitory computer readable medium storing instructions that,when executed by the one or more processors, cause the device to performfunctions comprising: displaying, via the user interface, an imagerepresenting first MRI data corresponding to biological tissue;receiving, via the user interface, first input identifying one or moretarget regions of the biological tissue to be mechanically fractionatedvia exposure to first ultrasound waves; applying, via the transducer,the first ultrasound waves to the one or more target regions, therebymechanically fractionating at least a portion of the one or more targetregions, wherein the first ultrasound waves are applied according to oneor more first parameters; contemporaneous to or after applying the firstultrasound waves, acquiring, via the MRI imaging system, second MRI datacorresponding to the biological tissue; determining, based on the secondMRI data, one or more second parameters for applying second ultrasoundwaves to the biological tissue; and applying, via the transducer, thesecond ultrasound waves to the biological tissue according to the one ormore second parameters.
 350. The device of claim 349, the functionsfurther comprising: prior to displaying the image, acquiring the firstMRI data by using the MRI imaging system.
 351. The device of claim 349,wherein the one or more second parameters are determined by one or moreprocessors.
 352. The device of claim 349, the functions furthercomprising: receiving, via the user interface, second input thatidentifies the one or more second parameters, wherein the one or moresecond parameters are determined based on the received second input.353. The device of claim 349, wherein the one or more second parametersare equal to the one or more first parameters.
 354. The device of claim349, wherein at least one parameter of the one or more second parametersis not equal to a corresponding parameter of the one or more firstparameters.
 355. The device of claim 349, wherein the second MRI dataindicates a change in signal intensity in comparison to the first MRIdata.
 356. The device of claim 355, wherein the indicated change insignal intensity includes one or more of: a positive change, a negativechange, a positive change resulting in a signal intensity that exceeds apredetermined threshold, or a negative change resulting in a signalintensity that is less than a predetermined threshold.